Countering gerrymandering in Pennsylvania with numerical models

Wired highlights a few academics who argued against gerrymandered political districts in Pennsylvania with models showing the low probability that the map is nonpartisan:

Then, Pegden analyzed the partisan slant of each new map compared to the original, using a well-known metric called the median versus mean test. In this case, Pegden compared the Republican vote share in each of Pennsylvania’s 18 districts. For each map, he calculated the difference between the median vote share across all the districts and the mean vote share across all of the districts. The bigger the difference, the more of an advantage the Republicans had in that map.

After conducting his trillion simulations, Pegden found that the 2011 Pennsylvania map exhibited more partisan bias than 99.999999 percent of maps he tested. In other words, making even the tiniest changes in almost any direction to the existing map chiseled away at the Republican advantage…

Like Pegden, Chen uses computer programs to simulate alternative maps. But instead of starting with the original map and making small changes, Chen’s program develops entirely new maps, based on a series of geographic constraints. The maps should be compact in shape, preserve county and municipal boundaries, and have equal populations. They’re drawn, in other words, in some magical world where partisanship doesn’t exist. The only goal, says Chen, is that these maps be “geographically normal.”

Chen generated 500 such maps for Pennsylvania, and analyzed each of them based on how many Republican seats they would yield. He also looked at how many counties and municipalities were split across districts, a practice the Pennsylvania constitution forbids “unless absolutely necessary.” Keeping counties and municipalities together, the thinking goes, keeps communities together. He compared those figures to the disputed map, and presented the results to the court…

Most of the maps gave Republicans nine seats. Just two percent gave them 10 seats. None even came close to the disputed map, which gives Republicans a whopping 13 seats.

It takes a lot of work to develop these models and they are based on particular assumptions as well as methods for calculations. Still, could a political side present a reasonable statistical counterargument?

Given both the innumeracy of the American population and some resistance to experts, I wonder how the public would view such models. On one hand, gerrymandering can be countered by simple arguments: the shapes drawn on the map are pretty strange and can’t truly represent any meaningful community. On the other hand, the models reinforce how unlikely these particular maps are. It isn’t just that the shapes are unusual; they are highly unlikely given various inputs that go into creating meaningful districts. Perhaps any of these argument are meaningless if your side is winning through the maps.

Computer models of the effects of gerrymandering on urban and rural voters

A new computer simulation of voting patterns by geography in the United States suggests gerrymandering may not be the cause of Republican majorities in the House:

To examine this hypothesis, we adapted a computer algorithm that we recently introduced in the Quarterly Journal of Political Science. It allows us to draw thousands of alternative, nonpartisan redistricting plans and assess the partisan advantage built into each plan. First we created a large number of districting plans (as many as 1,000) for each of 49 states. Then we predicted the probability that a Democrat or Republican would win each simulated district based on the results of the 2008 presidential election and tallied the expected Republican seats associated with each simulated plan.

The results were not encouraging for reform advocates. In the vast majority of states, our nonpartisan simulations produced Republican seat shares that were not much different from the actual numbers in the last election. This was true even in some states, like Indiana and Missouri, with heavy Republican influence over redistricting. Both of these states were hotly contested and leaned only slightly Republican over all, but of the 17 seats between them, only four were won by Democrats (in St. Louis, Kansas City, Gary and Indianapolis). While some of our simulations generated an additional Democratic seat around St. Louis or Indianapolis, most of them did not, and in any case, a vanishingly small number of simulations gave Democrats a congressional seat share commensurate with their overall support in these states.

The problem for Democrats is that they have overwhelming majorities not only in the dense, poor urban centers, but also in isolated, far-flung college towns, historical mining areas and 19th-century manufacturing towns that are surrounded by and ultimately overwhelmed by rural Republicans.

A motivated Democratic cartographer could produce districts that accurately reflected overall partisanship in states like these by carefully crafting the metropolitan districts and snaking districts along the historical canals and rail lines that once connected the nonmetropolitan Democratic enclaves. But such districts are unlikely to emerge by chance from a nonpartisan process. On the other hand, a Republican cartographer in these and other Midwestern states, along with some Southern states like Georgia and Tennessee, could do little to improve on the advantage bestowed by the existing human geography.

Perhaps this introduces a new strategy for political parties: the need to have more evenly distributed support rather than large clusters of support. But, as the bottom of the article notes, certain redistricting strategies like in Illinois or Maryland can provide Democrats some help in spreading out the effects of their urban voters.

Mapping the most gerrymandered districts

Buried in some of the election coverage this season was the story that this class of legislators will play an important role in the redistricting process. I love maps and here is a collection of maps of the “top ten most gerrymandered political districts in the United States.”

While there are some short descriptions of how these particular districts came to be defined, I’m sure there are some interesting stories about each case. If more voters knew that this is what districts could look like in the hands of legislators, would there be any outcry?